首页> 外文期刊>Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine >Derivation and internal validation of the screening to enhance prehospital identification of sepsis (SEPSIS) score in adults on arrival at the emergency department
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Derivation and internal validation of the screening to enhance prehospital identification of sepsis (SEPSIS) score in adults on arrival at the emergency department

机译:筛查的推导和内部验证,以增强到达急诊室后成人的院前败血症(SEPSIS)评分

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Prehospital recognition of sepsis may inform case management by ambulance clinicians, as well as inform transport decisions. The objective of this study was to develop a prehospital sepsis screening tool for use by ambulance clinicians. We derived and validated a sepsis screening tool, utilising univariable logistic regression models to identify predictors for inclusion, and multivariable logistic regression to generate the SEPSIS score. We utilised a retrospective cohort of adult patients transported by ambulance (n?=?38483) to hospital between 01 July 2013 and 30 June 2014. Records were linked using LinkPlus? software. Successful linkage was achieved in 33289 cases (86%). Eligible patients included adult, non-trauma, non-mental health, non-cardiac arrest cases. Of 33289 linked cases, 22945 cases were eligible. Eligible cases were divided into derivation (n?=?16063, 70%) and validation (n?=?6882, 30%) cohorts. The primary outcome measure was high risk of severe illness or death from sepsis, as defined by the National Institute for Health and Care Excellence Sepsis guideline. ‘High risk of severe illness or death from sepsis’ was present in 3.7% of derivation (n?=?593) and validation (n?=?254) cohorts. The SEPSIS score comprises the following variables: age, respiratory rate, peripheral oxygen saturations, heart rate, systolic blood pressure, temperature and level of consciousness (p??0.001 for all variables). Area under the curve was 0.87 (95%CI 0.85–0.88) for the derivation cohort, and 0.86 (95%CI 0.84–0.88) for the validation cohort. In an undifferentiated adult medical population, for a SEPSIS score?≥?5, sensitivity was 0.37 (0.31–0.44), specificity was 0.96 (0.96–0.97), positive predictive value was 0.27 (0.23–0.32), negative predictive value was 0.97 (0.96–0.97), positive likelihood value was 13.5 (9.7–18.73) and the negative likelihood value was 0.83 (0.78–0.88). This is the first screening tool developed to identify NICE high risk of severe illness or death from sepsis. The SEPSIS score is significantly associated with high risk of severe illness or death from sepsis on arrival at the Emergency Department. It may assist ambulance clinicians to identify those patients with sepsis in need of antibiotic therapy. However, it requires external validation, in clinical practice by ambulance clinicians, in an independent population.
机译:败血症的院前识别可能会通知救护车临床医生进行病例管理,并告知运输决策。这项研究的目的是开发一种可供救护临床医生使用的院前败血症筛查工具。我们推导并验证了脓毒症筛查工具,该工具利用单变量logistic回归模型来确定包含的预测因子,并使用多变量logistic回归来生成SEPSIS评分。我们采用回顾性队列研究方法,对2013年7月1日至2014年6月30日之间由救护车(n?=?38483)运送到医院的成年患者进行了记录。软件。 33289例病例中成功建立了联系(86%)。符合条件的患者包括成人,非创伤性,非心理健康,非心脏骤停病例。在33289例关联案件中,有22945例符合条件。符合条件的病例分为派生组(n = 16063,70%)和验证组(n = 6882,30%)。主要结果指标是脓毒症导致严重疾病或死亡的高风险,这是由美国国家卫生与医疗保健卓越脓毒症指南定义的。在衍生(n?=?593)和验证(n?=?254)队列的3.7%中,存在“因败血症导致严重疾病或死亡的高风险”。 SEPSIS分数包括以下变量:年龄,呼吸频率,外周血氧饱和度,心率,收缩压,体温和意识水平(所有变量的p <0.001)。对于派生队列,曲线下面积为0.87(95%CI 0.85-0.88),对于验证队列,曲线下面积为0.86(95%CI 0.84-0.88)。在未分化的成年医学人群中,对于SEPSIS分数≥5,敏感性为0.37(0.31-0.44),特异性为0.96(0.96-0.97),阳性预测值为0.27(0.23-0.32),阴性预测值为0.97 (0.96-0.97),正似然值为13.5(9.7-18.73),负似然值为0.83(0.78-0.88)。这是第一个用于识别NICE严重疾病或败血症死亡风险的筛查工具。 SEPSIS评分与到达急诊室时败血症导致的严重疾病或死亡的高风险显着相关。它可以帮助救护车临床医生确定需要抗生素治疗的败血症患者。但是,在救护车临床医生的临床实践中,它需要在独立人群中进行外部验证。

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